Testing Asynchronous Reactive Systems: Beyond the ioco framework

Adilson Bonifacio; Arnaldo Vieira Moura

doi:10.19153/cleiej.24.2.13

Testing Asynchronous Reactive Systems: Beyond the ioco framework

CLEI electronic journal ◽

10.19153/cleiej.24.2.13 ◽

2021 ◽

Vol 24 (2) ◽

Author(s):

Adilson Bonifacio ◽

Arnaldo Vieira Moura

Keyword(s):

Reactive Systems ◽

Model Based ◽

Systems Model ◽

Model Based Testing ◽

Special Cases ◽

Implementation Under Test ◽

Complete Test ◽

Manual Testing ◽

Special Case ◽

Test Suites

Manual testing can be rather time consuming and prone to errors specially when testing asynchronous reactive systems. Model based testing is a well-established approach to verify reactive systems specified by input output labeled transition systems (IOLTSs). One of the challenges stemming from model based testing is verifying conformance and, also, generating test suites, primarily when completeness is a required property. In order to check whether an implementation under test is in compliance with its respective specification one resorts to some form of conformance relation that guarantees the expected behavior of the implementations, given the behavior of the specification. The ioco relation is an example of such a conformance relation. In this work we study another conformance relation based on formal languages. We also investigate how to generate finite and complete test suites for IOLTS models, and discuss the complexity of the test generation mechanism under this new conformance relation. We also show that ioco is a special case of this new conformance relation. Further, we relate our contributions to more recent works, accommodating the restrictions of their classes of fault models as special cases, and we expose the complexity of generating any complete test suite that must satisfy their restrictions.

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Model-Based Testing of Reactive Systems

10.1007/b137241 ◽

2005 ◽

Cited By ~ 159

Keyword(s):

Reactive Systems ◽

Model Based ◽

Model Based Testing

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Model-Based Testing of Object-Oriented Reactive Systems with Spec Explorer

Formal Methods and Testing - Lecture Notes in Computer Science ◽

10.1007/978-3-540-78917-8_2 ◽

2008 ◽

pp. 39-76 ◽

Cited By ~ 85

Author(s):

Margus Veanes ◽

Colin Campbell ◽

Wolfgang Grieskamp ◽

Wolfram Schulte ◽

Nikolai Tillmann ◽

...

Keyword(s):

Reactive Systems ◽

Object Oriented ◽

Model Based ◽

Model Based Testing

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Requirements for information systems model-based testing

Proceedings of the 2007 ACM symposium on Applied computing - SAC '07 ◽

10.1145/1244002.1244306 ◽

2007 ◽

Cited By ~ 4

Author(s):

Pedro Santos-Neto ◽

Rodolfo Resende ◽

Clarindo Pádua

Keyword(s):

Information Systems ◽

Model Based ◽

Systems Model ◽

Model Based Testing

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Model-Based and Model-Free Social Cognition

10.31234/osf.io/ue6j2 ◽

2019 ◽

Author(s):

Leor M Hackel ◽

Jeffrey Jordan Berg ◽

Björn Lindström ◽

David Amodio

Keyword(s):

Reinforcement Learning ◽

Social Cognition ◽

Learning Strategies ◽

Memory Systems ◽

Learning Task ◽

Financial Advisors ◽

Model Based ◽

Model Free ◽

Systems Model ◽

Task Assessment

Do habits play a role in our social impressions? To investigate the contribution of habits to the formation of social attitudes, we examined the roles of model-free and model-based reinforcement learning in social interactions—computations linked in past work to habit and planning, respectively. Participants in this study learned about novel individuals in a sequential reinforcement learning paradigm, choosing financial advisors who led them to high- or low-paying stocks. Results indicated that participants relied on both model-based and model-free learning, such that each independently predicted choice during the learning task and self-reported liking in a post-task assessment. Specifically, participants liked advisors who could provide large future rewards as well as advisors who had provided them with large rewards in the past. Moreover, participants varied in their use of model-based and model-free learning strategies, and this individual difference influenced the way in which learning related to self-reported attitudes: among participants who relied more on model-free learning, model-free social learning related more to post-task attitudes. We discuss implications for attitudes, trait impressions, and social behavior, as well as the role of habits in a memory systems model of social cognition.

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